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20112022
most citedEvolutionary Multitasking for Multiobjective Continuous Optimization: Benchmark Problems, Performance Metrics and Baseline Results

134 citations · 333 across the 19 of their papers we have counts for

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18 papers · 1 filter

cs.NE20213 cited

Benchmark Problems for CEC2021 Competition on Evolutionary Transfer Multiobjectve Optimization

Songbai Liu, Qiuzhen Lin, Kay Chen Tan +1

Evolutionary transfer multiobjective optimization (ETMO) has been becoming a hot research topic in the field of evolutionary computation, which is based on the fact that knowledge…

cs.NE2021

Solving Large-Scale Multi-Objective Optimization via Probabilistic Prediction Model

Haokai Hong, Kai Ye, Min Jiang +2

The main feature of large-scale multi-objective optimization problems (LSMOP) is to optimize multiple conflicting objectives while considering thousands of decision variables at th…

cs.NE20213 cited

Principled Design of Translation, Scale, and Rotation Invariant Variation Operators for Metaheuristics

Ye Tian, Xingyi Zhang, Cheng He +2

In the past three decades, a large number of metaheuristics have been proposed and shown high performance in solving complex optimization problems. While most variation operators i…

cs.NE20213 cited

Manifold Interpolation for Large-Scale Multi-Objective Optimization via Generative Adversarial Networks

Zhenzhong Wang, Haokai Hong, Kai Ye +2

Large-scale multiobjective optimization problems (LSMOPs) are characterized as involving hundreds or even thousands of decision variables and multiple conflicting objectives. An ex…

cs.NE202014 cited

Progressive Tandem Learning for Pattern Recognition with Deep Spiking Neural Networks

Jibin Wu, Chenglin Xu, Daquan Zhou +2

Spiking neural networks (SNNs) have shown clear advantages over traditional artificial neural networks (ANNs) for low latency and high computational efficiency, due to their event-…

cs.NE2020

Synaptic Learning with Augmented Spikes

Qiang Yu, Shiming Song, Chenxiang Ma +2

Traditional neuron models use analog values for information representation and computation, while all-or-nothing spikes are employed in the spiking ones. With a more brain-like pro…